Chatbots that give nonsensical answers. Recommendation systems that miss the mark. Generative models that make things up.
Artificial intelligence is everywhere, but those who work with it every day know the truth: even the most advanced models can make mistakes.
And they often do — at the worst possible time: with customers, in production, in mission-critical scenarios.
👉 The question is no longer “How powerful is my model?”
But rather: “How reliable is it when it really matters?”
Testing an AI system is very different from testing a traditional feature.
Automated checks, synthetic datasets, predefined test cases...
They’re not enough anymore.
You need a new approach.
You need to involve the only intelligence that can truly spot errors: human intelligence.
We’ve put everything into a white paper focused on testing (and improving) AI models through crowdtesting:
✔ For those developing generative AI solutions
✔ For those who want to reduce bias, errors, inconsistencies
✔ For those who need real-world testing, with real people, in real contexts
📄 Download the white paper “AI under Test” to discover:
What no one tells you about AI testing
The biggest risks you should catch before going live
How human testers can help you build smarter, safer, more inclusive models